file
stringlengths 11
16
| type
stringclasses 7
values |
|---|---|
/mask/0.mp4 | mask |
/mask/1.mp4 | mask |
/mask/2.mp4 | mask |
/mask/3.mp4 | mask |
/mask/4.mp4 | mask |
/mask/5.mp4 | mask |
/mask/6.mp4 | mask |
/mask/7.mp4 | mask |
/mask/8.mp4 | mask |
/mask/9.mp4 | mask |
/monitor/0.mp4 | monitor |
/monitor/1.mp4 | monitor |
/monitor/2.mp4 | monitor |
/monitor/3.mp4 | monitor |
/monitor/4.mp4 | monitor |
/monitor/5.mp4 | monitor |
/monitor/6.mp4 | monitor |
/monitor/7.mp4 | monitor |
/monitor/8.mp4 | monitor |
/monitor/9.mp4 | monitor |
/outline/0.mp4 | outline |
/outline/1.mp4 | outline |
/outline/2.mp4 | outline |
/outline/3.mp4 | outline |
/outline/4.mp4 | outline |
/outline/5.mp4 | outline |
/outline/6.mp4 | outline |
/outline/7.mp4 | outline |
/outline/8.mp4 | outline |
/outline/9.mp4 | outline |
/print/0.mp4 | print |
/print/1.mp4 | print |
/print/2.mp4 | print |
/print/3.mp4 | print |
/print/4.mp4 | print |
/print/5.mp4 | print |
/print/6.mp4 | print |
/print/7.mp4 | print |
/print/8.mp4 | print |
/print/9.mp4 | print |
/print_cut/0.mp4 | print_cut |
/print_cut/1.mp4 | print_cut |
/print_cut/2.mp4 | print_cut |
/print_cut/3.mp4 | print_cut |
/print_cut/4.mp4 | print_cut |
/print_cut/5.mp4 | print_cut |
/print_cut/6.mp4 | print_cut |
/print_cut/7.mp4 | print_cut |
/print_cut/8.mp4 | print_cut |
/print_cut/9.mp4 | print_cut |
/real/0.mp4 | real |
/real/1.mp4 | real |
/real/2.mp4 | real |
/real/3.mp4 | real |
/real/4.mp4 | real |
/real/5.mp4 | real |
/real/6.mp4 | real |
/real/7.mp4 | real |
/real/8.mp4 | real |
/real/9.mp4 | real |
/silicone/0.mp4 | silicone |
/silicone/1.mp4 | silicone |
/silicone/2.mp4 | silicone |
/silicone/3.mp4 | silicone |
/silicone/4.mp4 | silicone |
/silicone/5.mp4 | silicone |
/silicone/6.mp4 | silicone |
/silicone/7.mp4 | silicone |
/silicone/8.mp4 | silicone |
/silicone/9.mp4 | silicone |
Web Camera Face Liveness Detection
The dataset consists of videos featuring individuals wearing various types of masks. Videos are recorded under different lighting conditions and with different attributes (glasses, masks, hats, hoods, wigs, and mustaches for men).
In the dataset, there are 7 types of videos filmed on a web camera:
- Silicone Mask - demonstration of a silicone mask attack (silicone)
- 2D mask with holes for eyes - demonstration of an attack with a paper/cardboard mask (mask)
- 2D mask - demonstration of an attack with a paper/cardboard silhouette (outline)
- Monitor Replay Attack - demonstration of an attack from a monitor (*monitor *)
- A4 Photo Attack - demonstration of a paper/cardboard A4 photo attack (print)
- A4 Photo with holes for eyes, nose and mouth - demonstration of a paper/cardboard A4 photo attack with cutouts for the eyes, nose, and mouth (print_cut)
- Real Video - demonstration of a real person's face (real)
The dataset allows researchers and developers in recognizing and analyzing facial expressions, anti-spoofing tasks, face detection, re-identification and face recognition tasks. The inclusion of various attributes and different lighting conditions aims to enhance the robustness and effectiveness of anti-spoofing models in real-world scenarios.
Full version of the dataset includes 30,000+ videos of people, leave a request on TrainingData to buy the dataset
Statistics for the dataset (gender and type of the attack):
Get the Dataset
This is just an example of the data
Leave a request on https://trainingdata.pro/datasets to learn about the price and buy the dataset
Content
The folder files includes:
- mask - includes videos of people wearing a 2D mask with holes for eyes,
- monitor - includes videos with demonstration of an attack from a monitor,
- outline - includes videos of people wearing a 2D mask,
- print - includes videos of people with an A4 photo,
- print_cut - includes videos of people with an A4 photo with holes for eyes, nose and mouth,
- real - includes real videos of people,
- silicone - includes videos of people wearing a silicone mask
File with the extension .csv
- file: link to access the file,
- type: type of the video (real, mask, outline, print, print_cut, silicone, monitor)
TrainingData provides high-quality data annotation tailored to your needs
More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets
TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets
keywords: ibeta level 1, ibeta level 2, liveness detection systems, liveness detection dataset, biometric dataset, biometric data dataset, biometric system attacks, anti-spoofing dataset, face liveness detection, deep learning dataset, face spoofing database, face anti-spoofing, face recognition, face detection, face identification, human video dataset, video dataset, presentation attack detection, presentation attack dataset, 2d print attacks, print 2d attacks dataset, printed 2d masks dataset, spoofing in 2D face recognition, facial masks, 2D face recognition systems, detecting face spoofing attacks, detecting presentation attacks, computer vision, surveillance face anti-spoofing, face liveness detection software solution, silicone masks attacks
- Downloads last month
- 60